TsRegressionPreventer::SetResult:
  adjusted: true
  havePreSegment: false
  preActiveAdjusted: false
  preActiveAdjustedWidth: 0.000000
  preOppositeAdjusted: false
  preOppositeAdjustedWidth: 0.000000
  havePostSegment: true
  postActiveAdjusted: true
  postActiveAdjustedWidth: 14.666557
  postOppositeAdjusted: true
  postOppositeAdjustedWidth: 3.666557
-----
Spline:
  hermite false
  preExtrap Held
  postExtrap Held
Knots:
  156.000000: 0.000000, Curve, preSlope 0.000000, postSlope -1.300000, preLen 0.000000, postLen 14.666557, auto false / false
  167.000000: 28.800000, Curve, preSlope 0.400000, postSlope 0.000000, preLen 3.666557, postLen 0.000000, auto false / false
-----
Ts.TsTest_SplineData(isHermite = False, preExtrapolation = Ts.TsTest_SplineData.Extrapolation(method = Ts.TsTest_SplineData.ExtrapHeld), postExtrapolation = Ts.TsTest_SplineData.Extrapolation(method = Ts.TsTest_SplineData.ExtrapHeld), knots = [Ts.TsTest_SplineData.Knot(time = float.fromhex('0x1.38p+7'), nextSegInterpMethod = Ts.TsTest_SplineData.InterpCurve, value = float.fromhex('0x0p+0'), preSlope = float.fromhex('0x0p+0'), postSlope = float.fromhex('-0x1.4cccccccccccdp+0'), preLen = float.fromhex('0x0p+0'), postLen = float.fromhex('0x1.d5546ea4f1444p+3'), preAuto = False, postAuto = False), Ts.TsTest_SplineData.Knot(time = float.fromhex('0x1.4ep+7'), nextSegInterpMethod = Ts.TsTest_SplineData.InterpCurve, value = float.fromhex('0x1.ccccccccccccdp+4'), preSlope = float.fromhex('0x1.999999999999ap-2'), postSlope = float.fromhex('0x0p+0'), preLen = float.fromhex('0x1.d551ba9621ce3p+1'), postLen = float.fromhex('0x0p+0'), preAuto = False, postAuto = False)])
-----
153.800000 0.000000
156.000000 0.000000
156.054726 -0.070973
156.109453 -0.141600
156.164179 -0.211879
156.218905 -0.281807
156.273632 -0.351380
156.328358 -0.420594
156.383085 -0.489447
156.437811 -0.557936
156.492537 -0.626056
156.547264 -0.693805
156.601990 -0.761179
156.656716 -0.828174
156.711443 -0.894787
156.766169 -0.961013
156.820896 -1.026850
156.875622 -1.092294
156.930348 -1.157340
156.985075 -1.221985
157.039801 -1.286224
157.094527 -1.350054
157.149254 -1.413471
157.203980 -1.476470
157.258706 -1.539047
157.313433 -1.601198
157.368159 -1.662917
157.422886 -1.724201
157.477612 -1.785046
157.532338 -1.845447
157.587065 -1.905399
157.641791 -1.964896
157.696517 -2.023935
157.751244 -2.082510
157.805970 -2.140616
157.860697 -2.198249
157.915423 -2.255402
157.970149 -2.312071
158.024876 -2.368248
158.079602 -2.423931
158.134328 -2.479113
158.189055 -2.533788
158.243781 -2.587951
158.298507 -2.641594
158.353234 -2.694713
158.407960 -2.747301
158.462687 -2.799351
158.517413 -2.850858
158.572139 -2.901814
158.626866 -2.952214
158.681592 -3.002048
158.736318 -3.051313
158.791045 -3.100000
158.845771 -3.148101
158.900498 -3.195610
158.955224 -3.242519
159.009950 -3.288820
159.064677 -3.334505
159.119403 -3.379567
159.174129 -3.423996
159.228856 -3.467785
159.283582 -3.510925
159.338308 -3.553407
159.393035 -3.595222
159.447761 -3.636361
159.502488 -3.676816
159.557214 -3.716575
159.611940 -3.755629
159.666667 -3.793969
159.721393 -3.831583
159.776119 -3.868463
159.830846 -3.904595
159.885572 -3.939971
159.940299 -3.974577
159.995025 -4.008403
160.049751 -4.041437
160.104478 -4.073667
160.159204 -4.105080
160.213930 -4.135664
160.268657 -4.165404
160.323383 -4.194289
160.378109 -4.222304
160.432836 -4.249434
160.487562 -4.275666
160.542289 -4.300984
160.597015 -4.325373
160.651741 -4.348817
160.706468 -4.371300
160.761194 -4.392806
160.815920 -4.413316
160.870647 -4.432814
160.925373 -4.451281
160.980100 -4.468698
161.034826 -4.485046
161.089552 -4.500306
161.144279 -4.514456
161.199005 -4.527477
161.253731 -4.539345
161.308458 -4.550038
161.363184 -4.559534
161.417910 -4.567807
161.472637 -4.574835
161.527363 -4.580590
161.582090 -4.585047
161.636816 -4.588178
161.691542 -4.589955
161.746269 -4.590348
161.800995 -4.589328
161.855721 -4.586862
161.910448 -4.582919
161.965174 -4.577464
162.019900 -4.570462
162.074627 -4.561878
162.129353 -4.551672
162.184080 -4.539806
162.238806 -4.526239
162.293532 -4.510928
162.348259 -4.493830
162.402985 -4.474896
162.457711 -4.454081
162.512438 -4.431333
162.567164 -4.406600
162.621891 -4.379826
162.676617 -4.350955
162.731343 -4.319927
162.786070 -4.286679
162.840796 -4.251145
162.895522 -4.213255
162.950249 -4.172937
163.004975 -4.130116
163.059701 -4.084709
163.114428 -4.036634
163.169154 -3.985800
163.223881 -3.932115
163.278607 -3.875478
163.333333 -3.815784
163.388060 -3.752922
163.442786 -3.686773
163.497512 -3.617213
163.552239 -3.544107
163.606965 -3.467313
163.661692 -3.386681
163.716418 -3.302046
163.771144 -3.213237
163.825871 -3.120067
163.880597 -3.022334
163.935323 -2.919825
163.990050 -2.812306
164.044776 -2.699524
164.099502 -2.581207
164.154229 -2.457055
164.208955 -2.326744
164.263682 -2.190146
164.318408 -2.046499
164.373134 -1.895545
164.427861 -1.736814
164.482587 -1.569789
164.537313 -1.393891
164.592040 -1.208477
164.646766 -1.012820
164.701493 -0.806103
164.756219 -0.587395
164.810945 -0.355631
164.865672 -0.109586
164.920398 0.152163
164.975124 0.431285
165.029851 0.729756
165.084577 1.049942
165.139303 1.394718
165.194030 1.767625
165.248756 2.173116
165.303483 2.616900
165.358209 3.106509
165.412935 3.652194
165.467662 4.268516
165.522388 4.977322
165.577114 5.813992
165.631841 6.842702
165.686567 8.204177
165.741294 10.362918
165.796020 20.933052
165.850746 23.401704
165.905473 24.437338
165.960199 25.236509
166.014925 25.832696
166.069652 26.308797
166.124378 26.699603
166.179104 27.026657
166.233831 27.304095
166.288557 27.541675
166.343284 27.746439
166.398010 27.923640
166.452736 28.077319
166.507463 28.210652
166.562189 28.326184
166.616915 28.425994
166.671642 28.511803
166.726368 28.585049
166.781095 28.646953
166.835821 28.698558
167.000000 28.800000
169.200000 28.800000
